Thermal error compensation method for machine center

In order to investigate the thermal behavior of a dual ball screw feed drive system of a precision boring machine tool, experimental study on and theoretical modeling of thermally induced error along with heat generation characteristics are conducted in this paper. Experiments are carried out on the machine tool to measure and collect the thermodynamic information with its feed drive system operating under different working conditions. Based on the real-time data of the thermal expansion of ball screw in the axial direction, relationships between the thermal error and axial elongation are established to predict the thermal error distribution. The results show that the thermal error varies with different working position through the ball screw length linearly and with working time nonlinearly. In addition, another simplified way to model thermal error is presented to overcome the difficulties existing in the ball screw feed drive system of which the axial elongation is hard to collect. Fuzzy clustering and linear regression methods are employed to carry out the theoretical modeling of thermal error and optimization to sift out the critical heat sources. With the temperature data of these critical heat generation points, the thermally induced error of the ball screw feed drive system can be predicted easily alternatively. Experiments under a different condition are preformed to verify both prediction and modeling methods. It turns out that the proposed prediction methods are effective and practical to be used in the machining process as well.

Section: Introductionmentioning

confidence: 99%

Experiment-based thermal error modeling method for dual ball screw feed system of precision machine tool

Shi

Zhang

Yang

et al. 2015

“…An important area of focus is related to the improvement in the accuracy of CNC machine tools [1][2][3]. The demand for manufacturing geometrically complex parts in various industries often calls for multi-axis machine tools to have a high machining accuracy [4]. Many factors affect machining accuracy including kinematics errors, thermal errors, cutting force induced errors, servo errors, and tool wear [5].…”

Section: Introductionmentioning

confidence: 99%

An analytical approach for crucial geometric errors identification of multi-axis machine tool based on global sensitivity analysis

Cheng

Zhao

Zhang

et al. 2014

Geometric errors directly affect the tool tip position, reduce machining accuracy, and are one of the most important errors of multi-axis machining tool. However, the geometric errors are intercoupling, and the measured values at different points vary and are stochastic. The identification of the most crucial geometric errors and the determination of a method to control them is a key problem to improve the machining accuracy of machine tool. To achieve this goal, a new analytical method, to identify crucial geometric errors for a multi-axis machine tool is proposed here based on multibody system (MBS) theory and global sensitivity analysis. The volumetric error modeling of multi-axis machine tool has been given by MBS theory, which describes the topological structure of multibody system simply and conveniently in a matrix. The stochastic characteristic of geometric errors is taken into consideration and Sobol global sensitivity analysis method is introduced to identify crucial geometric errors of machine tool. A vertical machining center is selected as an illustration example. The analysis results reveal that the analytical method presented in this paper can identify the crucial geometric errors and are helpful to improve the machining accuracy of multi-axis machine tool.

“…Zhang et al [13] applied a novel data processing method to optimize the thermal error prediction model based on the combination of grey model and neural network. Wu et al [14] introduced a real-time compensation approach for the thermal positioning error of a ball screw, in which multiple regression model was used to map the relationship between thermal errors and temperature variables. Wang et al [15] proposed a Newton interpolation-based modeling method to compensate the compound position errors of a milling center under different thermal states.…”

Section: Introductionmentioning

confidence: 99%

Integrated geometric and thermal error modeling and compensation for vertical machining centers

Yang

Fan

et al. 2014

The accuracy of machine tools is significantly affected by the geometric defect and thermal deformation of the mechanical components. This paper intends to provide a comprehensive compensation method for the integrated geometric and thermal errors of machine tools. Firstly, a synthesized volumetric model is established with homogeneous transformation matrix method, considering both the geometric and thermal effects. Then, in order to improve the modeling accuracy and efficiency of the geometric error components, an automatic modeling algorithm is proposed with the Chebyshev polynomial-based orthogonal least squares regression. Also, to improve the robustness of the thermal error models for the feed axes and the spindle system, the thermal effects caused by external ambient variation and internal heat sources are identified and modeled separately. Finally, an intelligent virtual compensation system is developed for machine tools based on the function of external machine original coordinate shift and fast Ethernet data interaction technique, and compensation tests on a vertical machining center showed that the position accuracy of the machine tool could be significantly improved after compensation.